Foreign direct investment in China : interrelationship between regional economic development and location determinants of foreign direct investment

Abstract

China has become an attractive destination for foreign direct investment (FDI). By the end of 2010, the accumulated FDI inflows in China reached USD (United States Dollars) 1,048.38 billion. FDI encourages economic growth by increasing capital formation, providing employment opportunities and introducing advanced technologies. However, due to its more favourable geographic location and the industrial development in the coastal region, more than 70 per cent of FDI inflows have gone to the coastal region, leaving the three inland regions, namely the northeast, central and western regions, to share the remainder. The issue of continued uneven regional distribution of FDI inflows in China has given rise to concerns regarding its effect on increasing regional economic development disparities. Two issues represent a substantial challenge to current policy-makers attempting to reduce regional disparity by guiding FDI inflows into less developed inland regions. The first relates to the identification of the location determinants of FDI inflows for individual regions, the second issue requires the identification of the most appropriate FDI for each region based on the region's comparative advantages. In order to address these two issues, multiple regression models based on panel data sets are used to examine the location determinants of FDI inflows in each region, as well as the combinations of location determinants of FDI inflows and different technology categories. The results confirm that FDI is attracted by different factors and these factors are specific to each region and FDI in technologies at difference levels of intensity are attracted by different location factors. Based on the empirical results, recommendations for policy-makers are provided, which will help them to better utilise FDI inflows based on regional comparative advantages and thus to reduce regional disparities.

Date of Award	2013
Original language	English